Suchergebnisse - Neural Computing and Applications
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Machine learning and deep learning applications in sports biomechanical analysis: A systematic scoping review of performance enhancement and injury prevention strategies (Anwendungen von maschinellem Lernen und Deep Learning in der sportbiomechanischen Analyse: Eine systematische Übersicht über Strategien zur Leistungssteigerung und Verletzungsprävention)
Dhahbi, W., Jebabli, N., Boujabli, M., Souaifi, M., Dergaa, I., Ezzdine, L. B.Veröffentlicht in ISBS Proceedings Archive: Vol. 43: Iss. 1 (2025)“… Methods: A comprehensive analysis synthesized evidence on AI methodologies applied to sports biomechanics across various contexts, including machine learning, neural networks, and deep learning approaches integrated with learning management systems. …”
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Exceeding limits in sports engineering: The bio-digital-material triad paradigm in the Asian sports performance revolution (Grenzen überschreiten im Sportingenieurwesen: Das Bio-Digital-Material-Triad-Paradigma in der asiatischen Sportleistungsrevolution)
Shen, Y., Liu, J., Li, J., Jing, H., Li, L.Veröffentlicht in Journal of Human Sport & Exercise (2025)“… This review article explores the innovative breakthroughs of exceeding limits in sports engineering within the context of the Asian sports performance revolution, with a particular focus on advancements in bio-enhancement technologies, neural interfaces, quantum computing, metamaterial equipment, digital twins, predictive medicine, gut microbiota, geopolitical technology, disaster medicine, and civilization-level technological spillovers. …”
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Evaluating the influence of sensor configuration and hyperparameter optimization on wearable-based knee moment estimation during running (Bewertung des Einflusses der Sensorkonfiguration und der Hyperparameteroptimierung auf die Schätzung des Kniemoments anhand von Wearables beim Laufen)
Höschler, L., Halmich, C., Schranz, C., Koelewijn, A. D., Schwameder, H.Veröffentlicht in International Journal of Computer Science in Sport (2025) -
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A narrative review of deep learning applications in sports performance analysis: current practices, challenges, and future directionsA narrative review of deep learning application... (Eine narrative Übersicht über Deep-Learning-Anwendungen in der Sportleistungsanalyse: aktuelle Praktiken, Herausforderungen und zukünftige Entwicklungen)
Jia, Y., Abdullah, N. A., Eliza, H., Lu, Q., Si, D., Guo, H., Wang, W.Veröffentlicht in BMC Sports Science, Medicine and Rehabilitation (2025)“… However, despite notable progress, challenges remain in standardizing methodologies, ensuring model reliability, and enhancing real-time application across various sports disciplines. Methods We conducted a systematic literature search of Web of Science Core Collection (WOS), China National Knowledge Infrastructure (CNKI), and Association for Computing Machinery Digital Library (ACM DL) for relevant studies published from 2015 to 2024, with no language restrictions. …”
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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review (Abbildung des taktischen Verhaltens und der kollektiven Dynamik im Fußball mit künstlicher Intelligenz: eine systematische Übersicht)
Teixeira, J. E., Maio, E., Afonso, P., Encarnação, S., Machado, G. F., Morgans, R., Barbosa, T. M., Monteiro, A. M., Forte, P., Ferraz, R., Branquinho, L.Veröffentlicht in Frontiers in Sports and Active Living (2025)“… Nevertheless, there are still challenges for the real practical application of AI-based techniques, as well as ethical regulation and the formation of professional profiles that combine sports science, data analytics, computer science, and coaching expertise. …”
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The analysis of gait patterns using a color camera and computer vision (Die Analyse von Gangmustern mithilfe einer Farbkamera und Computer Vision)
Batysheva, T. T., Tikhonov, S. V., Alekseeva, M. V., Peganskiy, D. A.Veröffentlicht in Theory and Practice of Physical Culture (2024)“… Objective of the study was to validate the approach for determining human walking metrics through the application of neural networks and computer vision techniques. …”
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BioMAT: An open-source biomechanics multi-activity transformer for joint kinematic predictions using wearable sensors (BioMAT: Ein Open-Source-Biomechanik-Multi-Aktivitäts-Transformator für Gelenkkinematik-Vorhersagen mit tragbaren Sensoren)
Sharifi-Renani, M., Mahoor, M. H., Clary, C. W.Veröffentlicht in Sensors (2023)“… Through wearable sensors and deep learning techniques, biomechanical analysis can reach beyond the lab for clinical and sporting applications. Transformers, a class of recent deep learning models, have become widely used in state-of-the-art artificial intelligence research due to their superior performance in various natural language processing and computer vision tasks. …”
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Determination of anthropometric indicators of the hand of athletes on the basis of computer vision (Bestimmung anthropometrischer Indikatoren der Hand von Sportlern auf der Grundlage von Computer Vision)
Pomerantsev, A. A., Bespyatkin, V. E., Travkov, D. A., Bakhtiarova, T. V.Veröffentlicht in Theory and Practice of Physical Culture (2023)“… The developed computer application with the working title "PalmAnthropometry_1.0" is based on the use of the MediaPipe open source framework, namely the Mediapipe Hands neural network, which allows you to determine the nodal points of the hand by analyzing the video stream. …”
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Analysis of movement and activities of handball players using deep neural networks (Analyse der Bewegungen und Aktivitäten von Handballspielern mithilfe von tiefen neuronalen Netzen)
Host, K., Pobar, M., Ivasic-Kos, M.Veröffentlicht in Journal of Imaging (2023)“… The aim of the paper is to explore the computer vision-based solutions for recognizing player actions that can be applied in unconstrained handball scenes with no additional sensors and with modest requirements, allowing a broader adoption of computer vision applications in both professional and amateur settings. …”
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3D ball localization from a single calibrated image (3D-Ball-Lokalisierung aus einem einzigen kalibrierten Bild)
Van Zandycke, G., De Vleeschouwer, C.Veröffentlicht in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2022) -
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Interaction classification with key actor detection in multi-person sports videos (Interaktionsklassifizierung mit Erkennung von Hauptakteuren in Sportvideos mit mehreren Personen)
Askari, F., Ramaprasad, R., Clark, J. J., Levine, M. D.Veröffentlicht in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2022)“… Our model consists of a Recurrent Neural Network (RNN) equipped with a time-varying attention mechanism. …”
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Construction of sports training performance prediction model based on a generative adversarial deep neural network algorithm (Konstruktion eines Modells zur Vorhersage der Trainingsleistung auf der Grundlage eines generativen adversen tiefen neuronalen Netzwerkalgorithmus)
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Synthesising 2D video from 3D motion data for machine learning applications (Synthese von 2-D-Video aus 3-D-Bewegungsdaten für Anwendungen des maschinellen Lernens )
Mundt, M., Oberlack, H., Goldacre, M., Powles, J., Funken, J., Morris, C., Potthast, W., Alderson, J.Veröffentlicht in Sensors (2022)“… To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames from historic 3D motion data. …”
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Clustering analysis algorithm of volleyball simulation based on radial fuzzy neural network (Clustering-Analyse-Algorithmus der Volleyball-Simulation auf der Grundlage des Radial Fuzzy Neural Network)
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Sports video analysis system based on dynamic image analysis (Sportvideo-Analysesystem basierend auf dynamischer Bildanalyse)
Li, Z., Ye, X., Liang, H.Veröffentlicht in Neural Computing and Applications (2023)“… Neural Computing and Applications …”
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Audio-video techniques for the analysis of players behaviour in Badminton matches (Audio-Video-Techniken für die Analyse des Spielerverhaltens bei Badmintonspielen)
Bosi, S.Veröffentlicht in POLITesi - Digital archive of PhD and post graduate theses (2022)“… Thanks to the great advances in computer vision and deep learning, it is nowadays possible to help manual annotators by means of automatic or semi-automatic multimedia analysis techniques. …”
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On the impact of computer vision algorithms on sport training automation: proof of concept for shadow boxing virtual instructor (Über die Auswirkungen von Bildverarbeitungsalgorithmen auf die Automatisierung des Sporttrainings: Konzeptnachweis für einen virtuellen Ausbilder im Schattenboxen)
Makarov, I., Petrov, S.Veröffentlicht 2021“… We overview several XR applications of deep convolutional neural networks to the opportunity for creating an automated sports training process. …”
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TTNet: Real-time temporal and spatial video analysis of table tennis (TTNet: zeitliche und räumliche Videoanalyse von Tischtennis in Echtzeit)
Voeikov, R., Falaleev, N., Baikulov, R.Veröffentlicht in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2020) -
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Improved soccer action spotting using both audio and video streams (Verbessertes Aufspüren von Aktionen im Fußball mit Audio- und Videostreams)
Vanderplaetse, B., Dupont, S.Veröffentlicht in IEEE/CVF Conference on Computer Vision and Pattern Recognition (2020) -
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Objects detection toward complicated high remote basketball sports by leveraging deep CNN architecture (Objekterkennung bei komplizierten Basketball-Aktionen mit hoher Reichweite durch Nutzung der Deep CNN-Architektur)
Liu, L.Veröffentlicht in Future Generation Computer Systems (2021)“… More specifically, we use the high discriminative power of the convolutional neural network to extract images to perform computational preprocessing for the recognition of each human motion image in the video stream. …”